使用 Cartopy 绘制适合海报大小的地图

Question

我的目标是制作一张带有旅行路线地图的海报。

您应该能够设置海报尺寸，即图形尺寸。

然后您提供长/纬度点列表。海报是水平还是垂直应取决于脚本，即适合提供的纬度/经度。

然后它应该以 pdf 格式返回海报，放大地图的相关部分，同时仍然填充整个画布。这是我几天来一直在努力解决的最后一部分。我想整个地图的长度需要改变以适应海报尺寸的比例，但我还没有做到。任何建议将非常感激 ！ 附言。我知道（bbox_inches='tight'），但它破坏了海报的总尺寸。

示例脚本：

import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import numpy as np

# Define the geographic locations (longitude, latitude)
points = np.array([
    (18.4241, -33.9249),
    (9.5375, 33.8869),  
    (-16.3151, 28.4682),
    (-9.1393, 38.7223),
    (-3.7038, 40.4168),
    (2.3522, 48.8566),
    (10.7522, 59.9139),
])

# Create figure and add a map in Mercator projection
fig, ax = plt.subplots(figsize=(10, 10), subplot_kw={'projection': ccrs.Mercator()})

# Calculate bounds
lon_min, lat_min = points.min(axis=0) - 1
lon_max, lat_max = points.max(axis=0) + 1

# Set extent based on points
ax.set_extent([lon_min, lon_max, lat_min, lat_max], crs=ccrs.PlateCarree())

# Plot points
ax.scatter(points[:, 0], points[:, 1], marker='o', color='red', transform=ccrs.Geodetic())

# Add coastlines for reference
ax.coastlines()

# Save the plot as a PDF
plt.savefig("map.pdf")

Answer 1

您可以使用 constrainedlayout 使轴填充图形，并使用 set_adjustable 更新数据限制，以便地图成为扩展轴的正确形状：

import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import numpy as np

# Define the geographic locations (longitude, latitude)
points = np.array([
    (18.4241, -33.9249),
    (9.5375, 33.8869),  
    (-16.3151, 28.4682),
    (-9.1393, 38.7223),
    (-3.7038, 40.4168),
    (2.3522, 48.8566),
    (10.7522, 59.9139),
])

# Create figure and add a map in Mercator projection
fig, ax = plt.subplots(figsize=(10, 10), subplot_kw={'projection': ccrs.Mercator()},
                       layout='constrained')

# Calculate bounds
lon_min, lat_min = points.min(axis=0) - 1
lon_max, lat_max = points.max(axis=0) + 1

# Set extent based on points
ax.set_extent([lon_min, lon_max, lat_min, lat_max], crs=ccrs.PlateCarree())

# Adjust the data limits so that the map fills the figure without stretching
ax.set_adjustable(adjustable='datalim')

# Plot points
ax.scatter(points[:, 0], points[:, 1], marker='o', color='red', transform=ccrs.Geodetic())

# Add coastlines for reference
ax.coastlines()

# Save the plot as a PDF
plt.savefig("map.png")